Spectral longwave atmospheric irradiance determination for site- and date-specific passive radiative cooling modeling

The effectiveness of passive radiative cooling is highly dependent on local atmospheric conditions, particularly the spectral distribution of downward longwave radiation. Many existing models rely on simplified or generalized assumptions such as fixed atmospheric profiles or empirical fits based on surface-level parameters that overlook important aspects of the vertical composition and spectral variability of the atmospheric column. In this work, we present a python-based workflow that generates site- and time-specific estimates of surface downward thermal radiation resolved into sixteen longwave spectral bands with hourly resolution. Our method combines reanalysis data from open ECMWF ERA5 and seasonal climatology data, and the RRTM_LW radiative transfer model, allowing for consistent incorporation of cloud effects based on the available input data. We demonstrate the application of this tool by constructing spectrally resolved Typical Meteorological Year (TMY) datasets and show how it can be used to improve energy balance calculations for radiative coolers. Comparisons with simplified approaches highlight the systematic errors arising when spectral and vertical atmospheric information are neglected.